The NBA has excited fans for generations. The athleticism of players created iconic moments, where fans have regularly got involved with NBA game odds to feel even more connected to each game’s outcome. Data analytics has played a big part in the transformation of the game with franchises hiring performance analysts in particular to look at the data from their games and training to help dictate how the team trains or is set out on game day. The sports analytics world has not been left behind on this and the concept of using real-time or historical NBA data to help decisions is now easier.
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Understanding Performance
With the metrics that help you can get into a team’s performance, you can identify how and why certain scenarios play out.
- Player Efficiency Rating
The Player Efficiency Rating is a rating of a player’s per-minute productivity during a game. Made from values for each of a players accomplishments during a game, they look at positives and negatives like free-throws compete or personal fouls. Because it is per-minute, this ensures we can have some level of comparison between players who may have a mismatch in total minutes on the court. It can also be adjusted to take in different styles, from high-octane sides to slower paced teams with less possession being part of their system. 15.00 is the league average, and you can then base some of your decisions from how players are compared to their rivals from this. It is a useful tool to put a value to the accomplishments of players on the court to make considered decisions when browsing the NBA odds. - True Shooting Percentage
Using True Shooting Percentage (TS%) metrics we can measure a player’s efficiency when shooting the ball from all areas of the court. It is the most accurate tool used over field goal percentage or free throw percentage as it considers all factors into its calculations. Players like Stephen Curry consistently post TS% and are easily identified as the players to rely upon in crunch situations as well as throughout the game if they can find space on the court to be dangerous. - Win Shares
This metric is a good way of identifying the strongest players on a side when it comes to getting results and can factor into your decisions on which team to back depending on the availability of players. Win Shares was invented by Justin Kubatko who created a value to be assigned to players based on their playing time and their offense and defense contributions. A Win Share is worth one-third of a team win. If a team wins 60 games, there are 180 ‘Win Shares’ to distribute amongst the players. It is a complex formula which tries to take factors like rebounds, blocks and efficiency as well as team success and much more to help quantify them into an easy-to-digest stat for wins. If a player with a high win share is unavailable for a game, it may be worth checking alternative replacement players.
Team-Level Analytics
Offensive and Defensive Efficiency is a key part of identifying the quality of a team and the potential outcomes of matches. These statistics are taken from ratings based on the number of points scored by or conceded by a team over 100 possessions. Identifying who is more efficient with the ball, and who is more difficult to score on can help with your decision making when it comes to betting on NBA lines. The odds will be stacked against a team who has a low defensive efficiency when playing a team with a high offensive efficiency.
Overvaluing Statistics
What must be remembered is that teams can adapt and develop their approach in season. While these metrics will help build an understanding of potential outcomes, teams are using them too to improve. Just because a team has a strong offensive efficiency doesn’t mean they will perform every game, athletes are human too, injuries can happen in game or the atmosphere the crowd builds could affect performance. Data analytics does give you the best chance of understanding the game which is approaching. Without data analytics we would be betting with our gut every time. The numbers help us gain a strong understanding of how teams and players are performing and what we could expect in future games too. Make sure you understand what the data is telling you, the numbers need to be understood to make best use of them. Do you research and give yourself the best chance of predicting the right outcomes?